Genetic and seasonal determinants of vitamin D status in Confederated Salish and Kootenai Tribes (CSKT) participants

Background: Vitamin D is a hormone produced in the skin upon ultraviolet B (UVB) radiation. Vitamin D is a crucial regulator of calcium and phosphate levels for bone mineralization and other physiological roles. Vitamin D levels vary globally in human populations due to genetics, geography, and other demographic factors. It is estimated that 20-85 % of the variability in vitamin D levels is driven by genetic variation. To improve our understanding of contributors to vitamin D levels, we conducted a candidate-gene study in partnership with the Confederated Salish and Kootenai Tribes (CSKT). Methods: We recruited 472 CSKT study participants on the Flathead Reservation in Montana. Demographic factors included age, BMI, and gender (185 male and 287 female; ≥ 18 years old). Genomic DNA and plasma were isolated from whole blood. We sequenced 14 vitamin D regulatory candidate genes: CASR, CUBN, CYP2R1, CYP3A4,CYP24A1, CYP27B1, DHCR7, GC, RXRA, RXRB, RXRG, SULT2A1, UGT1A4, and VDR. We also measured plasma levels of vitamin D and vitamin D metabolites by liquid chromatography/mass-spectrometry (LC/MS), including the clinical marker of vitamin D status, 25-hydroxyvitamin D3 [25(OH)D3]. We tested demographic factors as well as common and rare genetic variants for statistical associations with vitamin D levels using bioinformatics software and R statistical programming language code. Results: We identified 7,370 total genetic variants with 8% (n = 585) of them being novel. We identified 60 genetic variants that may be of clinical significance (disease associated or predicted to influence medication response). Vitamin D levels were below sufficiency [25(OH)D3 + 25(OH)D2 levels \u3c 20 ng/mL] in 56 % of CSKT participants across the year. We observed seasonal vitamin D and metabolite level fluctuations in a seasonal, sinusoidal statistical model with peak concentrations in June – August and trough concentrations in December – February. In linear regression analysis, we found that age, BMI, season, and 5 variants in CUBN and CYP3A4 were significantly associated with 25(OH)D3 concentration (p-value\u3c 0.05). In logistic regression, we found that 4 variants in CUBN, CYP3A4, and UGT1A4 were associated with 25(OH)D sufficiency status [25(OH)D3 + 25(OH)D2 levels of 20 ng/mL] (p-value\u3c 0.05). Multivariate linear regression analysis revealed that genetic variation alone explained ~13% of the variability in 25(OH)D3 concentration in CSKT participants. Genetic variation and environmental factors together explained ~23 % of the variability in 25(OH)D3 concentration in CSKT participants. It is likely that genetic variation in additional genes and other environmental factors (e.g., dietary vitamin D intake) that were not included in this study explain the remaining variability in 25(OH)D3 concentration. Conclusion: This research addresses the need for increased inclusion of American Indian and Alaska Natives in precision medicine health research. We are the first to describe the contribution of season and genetics to vitamin D levels in an American Indian population. Our next steps will be to use these findings to perform mechanistic studies and develop interventional strategies for the CSKT people

Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

Telomere length is a risk factor in disease and the dynamics of telomere length are crucial to our understanding of cell replication and vitality. The proliferation of whole genome sequencing represents an unprecedented opportunity to glean new insights into telomere biology on a previously unimaginable scale. To this end, a number of approaches for estimating telomere length from whole-genome sequencing data have been proposed. Here we present Telomerecat, a novel approach to the estimation of telomere length. Previous methods have been dependent on the number of telomeres present in a cell being known, which may be problematic when analysing aneuploid cancer data and non-human samples. Telomerecat is designed to be agnostic to the number of telomeres present, making it suited for the purpose of estimating telomere length in cancer studies. Telomerecat also accounts for interstitial telomeric reads and presents a novel approach to dealing with sequencing errors. We show that Telomerecat performs well at telomere length estimation when compared to leading experimental and computational methods. Furthermore, we show that it detects expected patterns in longitudinal data, repeated measurements, and cross-species comparisons. We also apply the method to a cancer cell data, uncovering an interesting relationship with the underlying telomerase genotype

GWAS meta-analysis of intrahepatic cholestasis of pregnancy implicates multiple hepatic genes and regulatory elements

Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy-specific liver disorder affecting 0.5–2% of pregnancies. The majority of cases present in the third trimester with pruritus, elevated serum bile acids and abnormal serum liver tests. ICP is associated with an increased risk of adverse outcomes, including spontaneous preterm birth and stillbirth. Whilst rare mutations affecting hepatobiliary transporters contribute to the aetiology of ICP, the role of common genetic variation in ICP has not been systematically characterised to date. Here, we perform genome-wide association studies (GWAS) and meta-analyses for ICP across three studies including 1138 cases and 153,642 controls. Eleven loci achieve genome-wide significance and have been further investigated and fine-mapped using functional genomics approaches. Our results pinpoint common sequence variation in liver-enriched genes and liver-specific cis-regulatory elements as contributing mechanisms to ICP susceptibility

Publisher Correction: Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

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Bi-allelic Loss-of-Function CACNA1B Mutations in Progressive Epilepsy-Dyskinesia.

The occurrence of non-epileptic hyperkinetic movements in the context of developmental epileptic encephalopathies is an increasingly recognized phenomenon. Identification of causative mutations provides an important insight into common pathogenic mechanisms that cause both seizures and abnormal motor control. We report bi-allelic loss-of-function CACNA1B variants in six children from three unrelated families whose affected members present with a complex and progressive neurological syndrome. All affected individuals presented with epileptic encephalopathy, severe neurodevelopmental delay (often with regression), and a hyperkinetic movement disorder. Additional neurological features included postnatal microcephaly and hypotonia. Five children died in childhood or adolescence (mean age of death: 9 years), mainly as a result of secondary respiratory complications. CACNA1B encodes the pore-forming subunit of the pre-synaptic neuronal voltage-gated calcium channel Cav2.2/N-type, crucial for SNARE-mediated neurotransmission, particularly in the early postnatal period. Bi-allelic loss-of-function variants in CACNA1B are predicted to cause disruption of Ca2+ influx, leading to impaired synaptic neurotransmission. The resultant effect on neuronal function is likely to be important in the development of involuntary movements and epilepsy. Overall, our findings provide further evidence for the key role of Cav2.2 in normal human neurodevelopment.MAK is funded by an NIHR Research Professorship and receives funding from the Wellcome Trust, Great Ormond Street Children's Hospital Charity, and Rosetrees Trust. E.M. received funding from the Rosetrees Trust (CD-A53) and Great Ormond Street Hospital Children's Charity. K.G. received funding from Temple Street Foundation. A.M. is funded by Great Ormond Street Hospital, the National Institute for Health Research (NIHR), and Biomedical Research Centre. F.L.R. and D.G. are funded by Cambridge Biomedical Research Centre. K.C. and A.S.J. are funded by NIHR Bioresource for Rare Diseases. The DDD Study presents independent research commissioned by the Health Innovation Challenge Fund (grant number HICF-1009-003), a parallel funding partnership between the Wellcome Trust and the Department of Health, and the Wellcome Trust Sanger Institute (grant number WT098051). We acknowledge support from the UK Department of Health via the NIHR comprehensive Biomedical Research Centre award to Guy's and St. Thomas' National Health Service (NHS) Foundation Trust in partnership with King's College London. This research was also supported by the NIHR Great Ormond Street Hospital Biomedical Research Centre. J.H.C. is in receipt of an NIHR Senior Investigator Award. The research team acknowledges the support of the NIHR through the Comprehensive Clinical Research Network. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, Department of Health, or Wellcome Trust. E.R.M. acknowledges support from NIHR Cambridge Biomedical Research Centre, an NIHR Senior Investigator Award, and the University of Cambridge has received salary support in respect of E.R.M. from the NHS in the East of England through the Clinical Academic Reserve. I.E.S. is supported by the National Health and Medical Research Council of Australia (Program Grant and Practitioner Fellowship)

Expansion and evolution of the R programming language

Languages change over time, driven by creation of new words and cultural pressure to optimize communication. Programming languages resemble written language but communicate primarily with computer hardware rather than a human audience. I tested whether there were detectable changes over time in use of R, a mature, open-source programming language used for scientific computing. Across 393 142 GitHub repositories published between 2014 and 2021, I extracted 143 409 288 R functions, programming ‘verbs’, pairing linguistic and ecological analyses to detect change to diversity and composition of functions used over time. I found the number of R functions in use increased and underwent substantial change, driven primarily by the popularity of the ‘tidyverse' collection of community-written extensions. I provide evidence that users can change the nature of programming languages, with patterns that match known processes from natural languages and genetic evolution. In R, there appear to be selective pressures for increased analytic complexity and R functions in decline that are not yet extinct (extinction debts). R's evolution towards the tidyverse may also represent the start of a division into two distinct dialects, which may impact the readability and continuity of analytic and scientific inquiries codified in R, as well as the language's future

Increased extinction in the emergence of novel ecological communities

Environmental change is transforming ecological assemblages into new configurations, resulting in novel communities. We developed a robust methodology to detect novel communities, examine patterns of emergence, and quantify probabilities of local demographic turnover in transitions to and from novel communities. Using a global dataset of Cenozoic marine plankton communities, we found that the probability of local extinction, origination, and emigration during transitions to a novel community increased two to four times that of background community changes. Although rare, novel communities were five times more likely than chance to shift into another novel state. For marine plankton communities at a 100,000-year time grain, novel communities were sensitive to further extinctions and substantial community change

Recurrence quantification for the analysis of coupled processes in aging

Objectives: Aging is a complex phenomenon, with numerous simultaneous processes that interact with each other on a moment-to-moment basis. One way to quantify the interactions of these processes is by measuring how much a process is similar to its own past states or the past states of another system through the analysis of recurrence. This paper presents an introduction to recurrence quantification analysis (RQA) and cross-recurrence quantification analysis (CRQA), two dynamical systems analysis techniques that provide ways to characterize the self-similar nature of each process and the properties of their mutual temporal co-occurrence. Method: We present RQA and CRQA and demonstrate their effectiveness with an example of conversational movements across age groups. Results: RQA and CRQA provide methods of analyzing the repetitive processes that occur in day-to-day life, describing how different processes co-occur, synchronize, or predict each other and comparing the characteristics of those processes between groups. Discussion: With intensive longitudinal data becoming increasingly available, it is possible to examine how the processes of aging unfold. RQA and CRQA provide information about how one process may show patterns of internal repetition or echo the patterning of another process and how those characteristics may change across the process of aging

Potential mechanisms of coexistence in closely related forbs

The stable coexistence of very similar species has perplexed ecologists for decades and has been central to the development of coexistence theory. According to modern coexistence theory, species can coexist stably (i.e. persist indefinitely with no long-term density trends) as long as species' niche differences exceed competitive ability differences, even if these differences are very small. Recent studies have directly quantified niche and competitive ability differences in experimental communities at small spatial scales, but provide limited information about stable coexistence across spatial scales in heterogeneous natural communities. In this study, we use experimental and observational approaches to explore evidence for niche and competitive ability differences between two closely related, ecologically similar and widely coexisting annual forbs: Trachymene cyanopetala and T. ornata. We experimentally tested for stabilizing niche differences and competitive ability differences between these species by manipulating species' frequencies, under both well-watered and water-stressed conditions. We considered these experimental results in light of extensive field observations to explore evidence of niche segregation at a range of spatial scales. We found little evidence of intra-specific stabilization or competitive ability differences in laboratory experiments while observational studies suggested niche segregation across pollinator assemblages and small-scale microclimate heterogeneity. Though we did not quantify long-term stabilization of coexisting populations of these species, results are consistent with expectations for stable coexistence of similar species via a spatial storage effect allowing niche differences to overcome even small (to absent) competitive ability differences